Surface Scan Projection for Local Variation Shim Design
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Solution Overview
Problem
Existing methods struggle to accurately determine local variations in complex surfaces of fabricated components that need to mate with further components during assembly, particularly when these surfaces lack a CAD representation or are too complex for simple mappings.
Innovation Solution
A method and system that projects surface scan data onto a coordinate system perpendicular to the average normal vector, using local average normals to filter and generate a shim design that fills local variations, ensuring a smooth mating surface during assembly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional areal filtering methods are used for planar or cylindrical surfaces, then the filtering process is simple and well-established, but the method cannot accurately handle complex surfaces without CAD representation or with irregular geometries
Solution Approach 1:
The method segments the surface analysis process into discrete steps: acquiring point cloud data, determining local normal vectors at each point, projecting points onto planes perpendicular to these normals, and filtering deviations. This segmentation allows the method to handle complex surfaces without requiring global coordinate system alignment, making the approach adaptable to various surface geometries while keeping each step computationally manageable
Solution Approach 2:
The invention applies local quality by determining normal vectors and performing filtering operations at each individual point or small neighborhood on the surface, rather than applying a global coordinate transformation. This local approach allows the method to adapt to varying surface geometries at different locations, handling both simple and complex surfaces uniformly without requiring CAD models
2Manufacturing precision
If complex mapping functions are developed to map (X, Y, Z) surfaces to (U, V) planes, then surface filtering can be performed, but the process becomes impractical for surfaces without CAD representation or with complex geometries
Solution Approach 1:
The method extracts the essential information needed for filtering by determining local normal vectors at each surface point and using these to define local XY planes. Instead of requiring a complex global mapping function, the approach extracts and uses only the local geometric information (normal vectors) needed to perform filtering operations, simplifying the implementation while maintaining measurement accuracy for complex surfaces
Solution Approach 2:
The invention creates a simplified digital representation of the surface by projecting points onto local XY planes defined by normal vectors, rather than requiring the original complex surface geometry or CAD model. This copied representation in a local coordinate system allows standard filtering techniques to be applied accurately without dealing with the complexity of the original surface geometry
3Productivity
If surface scan data is directly filtered without coordinate system transformation, then the process is efficient, but accurate filtering cannot be achieved on surfaces with varying orientations and complex geometries
Solution Approach 1:
The method introduces dynamics by adapting the coordinate system orientation at each point based on the local normal vector, rather than using a fixed global coordinate system. This dynamic adaptation of the local XY plane orientation to match the surface geometry at each point enables accurate filtering of surfaces with varying orientations while maintaining computational efficiency through localized operations
Data Source
Figure 1
Figure 2A~2D
Figure 3A~3B
AI summary
A method for determining local variations in a surface of a fabricated component includes comparing surface scan data for the fabricated component represented in a first XYZ coordinate system to surface design data for the surface of the fabricated component, determining deviation data values for the surface based on the comparing, wherein the deviation data values are represented as deviation data points, selecting a first data point and neighboring data points from the deviation data points, determining an average normal vector for the first data point based on normal vectors of the first data point and the neighboring data points, defining an XY plane of a second XYZ coordinate system perpendicular to the average normal vector for the first data point, and projecting the first data point and the neighboring data points from the first XYZ coordinate system onto the XY plane of the second XYZ coordinate system.